u/catap

I had spend a lot of time to thinking about proper conversion from cvs to git and so far I'm at the point where I think that it can't be done without loosing of some information, overcommitting things or adding "cleanup commits" and similar hacks.

Why?

CVS keeps state per file and GIT a global one per repository.

When someone tagging something he tags whole repo state in case of GIT and some files (or all) in case of CVS.

What is the larger example of some conceptual issues.

Unfortently google. Everything else worse.

If you use OpenBSD as host system, when no. Qemu in ports -current has everythign already, plus all -current kernel has all requires patches to work with my obsd.sh out of the box.

I do have https://github.com/catap/obsd.sh and working time to time to support the rest of platforms.

It needs patches, but majority of platforms works well.

Maybe it can help you somehow extend supported platforms.

Thus, here a Blog Post where I keep actual qemu args in easy to copy and past way: https://kirill.korins.ky/articles/openbsd-under-qemu/

Lates 90s was a bit more than 20 years ago 🙈

Mainly depends on that you're searching for.

I had re-tested nearly the following as my main search engine: Kagi, Google, Bing, DuckDuckGo, SearXNG (priv.au), Mojeek, Brave Search, Qwant and Swisscows.

Well... For my everyday searches, Kagi gives the best search results. Not sure why, but it does.

I suggest just to try all of them for a few days and pick that feels better.

Kagi has "interface" to read random small web's article: https://kagi.com/smallweb

And Marginalia has explore feature: https://marginalia-search.com/explore

So far it is the only more or less structurally chaotic way to look at it I know

Actually it still exists. But it is on the edge of internet.

Sometimes it's called small-web.

Marginalia Search has its own list of small websites public available here: https://github.com/MarginaliaSearch/submit-site-to-marginalia-search

The same about Kagi: https://github.com/kagisearch/smallweb

But it is not structured that actually the way it was

Yes, indeed.

It was like switching to Google 20+ years ago.

The same emotion.

I have had an account since November 2023.

Over the last few weeks, I have tried using the following as my main search engine: Kagi, Google, DuckDuckGo, SearXNG (priv.au), Mojeek, Brave Search, Qwant, and Swisscows.

Well... For my everyday searches, Kagi gives the best search results. Not sure why, but it does.

The only thing is the UI, but that is personal. I like Qwant more, but it lacks features like selecting a region, as DuckDuckGo and Kagi allow. And its quality sucks, at least for me.

Verpflichtungserklärung is hard things.

If simplified it says that person will cover unlimited financial obligations on your behalf for 5 years without any way to withdraw.

Here major point: I try it to complex algorithmic tasks and thinking for 30-40 minutes for 5.2 model was usual.

So, my use case is probably not they had targeted at all.

I'm playing with it a bit.

Here notes from yesterday: https://www.reddit.com/r/codex/comments/1qxm5yc/ive_already_switched_back_to_gpt52_high_from/o40bcdp/

During today more agresivly work I had discovered the proof that 5.3-codex was made in quite a rush, for example here no dedicated prompt for it: https://github.com/openai/codex/tree/main/codex-rs/core

Also, I noticed that it completley ignore all wording in ~/.codex/AGENTS.md

And, what's more important, it's dump.

On my playground task (quite complicated) it hits the wall and started to hack its win.

Yeah, codex-5.3-xhigh seems love to hack its win.

The only plus that it fast. But it's all.

So, 5.2-xhigh still the goat, and if your task algorithmic unique which needs logic, codex-5.3-xhigh way worst whan codex-5.2-xhigh.

Because I had insomia, here anohter test.

I've asked models to add feature which clearly exists if you read the unit test and input contains a typo which makes it odd.

codex-5.2-xhigh: asked clarifications about a typo before it write any code after 3m21s

Token usage: total=47.490 input=42.917 (+ 183.168 cached) output=4.573 (reasoning 3.648)

codex-5.3-xhigh: tried to wite code with short cut for feature after 3m04s

Token usage: total=35.378 input=22.324 (+ 133.760 cached) output=13.054 (reasoning 11.875)

gpt-5.2-xhigh: tried to write code after 17m31s of thinking:

Token usage: total=96.202 input=48.910 (+ 448.640 cached) output=47.292 (reasoning 46.080)

So, they still can't understand already existed feature :(

A small benchmark. I have some fairly complex code with a lot of logic. The task is to increase the coverage of the unit test by reaching one specific function.

codex-5.3-xhigh: initial input plus six corrections. One attempt was clearly a hack, involving a direct call to the function. We also had that short chat with that model:

-- I don't buy your explanation. I wrote that parser.

-- You’re right. I’ll drop the fresh-parser.

Token usage: total=341.843 input=253.800 (+ 4.520.448 cached) output=88.043 (reasoning 80.533)

codex-5.2-xhigh: initial input, asked is it ok to make clear hack or you need a normal way? Plus three correction and has more less the same result like codex-5.3-xhigh but a bit wordy, which was improved to an actual result via 4th correction.

Token usage: total=405.962 input=304.835 (+ 4.670.336 cached) output=101.127 (reasoning 91.904)

gpt-5.2-xhigh: initial input plus two correction. Proved me that here a dead code path (!) exists.

Token usage: total=603.580 input=397.747 (+ 7.261.952 cached) output=205.833 (reasoning 192.403)

Keep in mind: this test was about for 3-4 hours long.

Do I see differences? I think gpt-5.2-xhigh is indeed very long working, but, indeed, worth it. And codex-5.3 is better than codex-5.2

Here I keep an actual status: https://kirill.korins.ky/articles/openbsd-on-honor-magicbook-art-14-snapdragon/

Unfortently Apple implemented their own way.

And this implementation includes "pairing" via idevicepair or similar tools.

It generates or uses hardcoded key to pair a computer with this iphone, and user must to unblock it and click "ok".

MuseBook aka DC Roma Laptop II which is very similar to Banama Pi can be, partially, botted with OpenBSD kernel.

It needs more love, but I almost sure that I'll figure it out.

Proof: https://www.instagram.com/p/DRBBYpsCKVr/

Huawei Matebook X 2020?

By Intel GPUs, does that include ARC GPUs?

If it needs xe driver at Linux it won't work. If i915 yes, it quite possible works.

Private ejabberd?

I had bought last December HONOR MagicBook Art 14 Snapdragon, which I thought is fanless but it truns to be just with quite fans.

Unfortently I hear fans of this machine.

But after some working it can be used at OpenBSD:https://kirill.korins.ky/articles/openbsd-on-honor-magicbook-art-14-snapdragon/ , and because it isn't a daily driver, more like a toy, I haven't invested much time for future support of this machine.

I absolutley fine with arm64 or risc64 or mips64 laptop if it on platform / SoC which can run Linux or something opensourced.